Acute promyelocytic leukaemia is characterized by stable incidence and improved survival that is restricted to patients managed in leukaemia referral centres: a pan-Canadian epidemiological study
Bibliographic record
Abstract
Timely diagnosis and care are major determinants of the outcome in acute promyelocytic leukaemia (APL), a malignancy whose incidence may be increasing. The Canadian Cancer Registry (CCR) and health system represent valuable settings to study APL epidemiology. We analysed the CCR, which contains data on all Canadians with APL. To provide clinical information lacking in the CCR, we obtained data from five leukaemia referral centres during a similar time period. Between 1993 and 2007, there were 399 APL in Canada. Age-standardized incidence was 0·083/100,000 and was stable over time. The early death (ED) rate was 21·8% (10·6% in patients <50 years old and 35·5% for those aged >50 years), with no improvement over time. Five-year overall survival (OS) was 54·6% (73·3% in patients <50 years; 29·1% older patients). In the referral cohort, 131 patients were diagnosed between 1999 and 2010. ED was 14·6% and 2-year OS was 76·5%. Within this cohort, ED and OS improved over time, although advanced patient age remained an adverse determinant of OS. In Canada, APL incidence is unexpectedly low and temporally stable. ED was higher than reported in clinical trials, but similar to reports from other registries. In contrast, ED was lower in referral centres and improved with time.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.013 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".